{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "from vega_datasets import data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>petalLength</th>\n",
       "      <th>petalWidth</th>\n",
       "      <th>sepalLength</th>\n",
       "      <th>sepalWidth</th>\n",
       "      <th>species</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>5.1</td>\n",
       "      <td>3.5</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>4.9</td>\n",
       "      <td>3.0</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1.3</td>\n",
       "      <td>0.2</td>\n",
       "      <td>4.7</td>\n",
       "      <td>3.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1.5</td>\n",
       "      <td>0.2</td>\n",
       "      <td>4.6</td>\n",
       "      <td>3.1</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   petalLength  petalWidth  sepalLength  sepalWidth species\n",
       "0          1.4         0.2          5.1         3.5  setosa\n",
       "1          1.4         0.2          4.9         3.0  setosa\n",
       "2          1.3         0.2          4.7         3.2  setosa\n",
       "3          1.5         0.2          4.6         3.1  setosa\n",
       "4          1.4         0.2          5.0         3.6  setosa"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "iris = data('iris')\n",
    "iris.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x1210a1860>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(iris.petalLength, iris.sepalWidth)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Need to manually specify color map \n",
    "color_map =  dict(zip(iris.species.unique(), ['blue', 'green', 'red']))\n",
    "\n",
    "# Adding color involves for loop and groupby\n",
    "for species, group in iris.groupby('species'):\n",
    "    plt.scatter(group.petalLength, group.sepalWidth,color=color_map[species],label=species)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'sepalLength')"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Need to manually specify color map \n",
    "color_map =  dict(zip(iris.species.unique(), ['blue', 'green', 'red']))\n",
    "\n",
    "# Adding color involves for loop and groupby\n",
    "for species, group in iris.groupby('species'):\n",
    "    plt.scatter(group.petalLength, group.sepalWidth,color=color_map[species],label=species)\n",
    "\n",
    "# Need to manually add legend and field titles\n",
    "plt.legend(frameon=True, title='species')\n",
    "plt.xlabel('petalLength')\n",
    "plt.ylabel('sepalLength')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "import altair as alt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.vegalite.v2+json": {
       "$schema": "https://vega.github.io/schema/vega-lite/v2.6.0.json",
       "config": {
        "view": {
         "height": 300,
         "width": 400
        }
       },
       "data": {
        "name": "data-a264acbd6e539a8b3afc0cb5f240fb57"
       },
       "datasets": {
        "data-a264acbd6e539a8b3afc0cb5f240fb57": [
         {
          "petalLength": 1.4,
          "petalWidth": 0.2,
          "sepalLength": 5.1,
          "sepalWidth": 3.5,
          "species": "setosa"
         },
         {
          "petalLength": 1.4,
          "petalWidth": 0.2,
          "sepalLength": 4.9,
          "sepalWidth": 3,
          "species": "setosa"
         },
         {
          "petalLength": 1.3,
          "petalWidth": 0.2,
          "sepalLength": 4.7,
          "sepalWidth": 3.2,
          "species": "setosa"
         },
         {
          "petalLength": 1.5,
          "petalWidth": 0.2,
          "sepalLength": 4.6,
          "sepalWidth": 3.1,
          "species": "setosa"
         },
         {
          "petalLength": 1.4,
          "petalWidth": 0.2,
          "sepalLength": 5,
          "sepalWidth": 3.6,
          "species": "setosa"
         },
         {
          "petalLength": 1.7000000000000002,
          "petalWidth": 0.4,
          "sepalLength": 5.4,
          "sepalWidth": 3.9,
          "species": "setosa"
         },
         {
          "petalLength": 1.4,
          "petalWidth": 0.30000000000000004,
          "sepalLength": 4.6,
          "sepalWidth": 3.4,
          "species": "setosa"
         },
         {
          "petalLength": 1.5,
          "petalWidth": 0.2,
          "sepalLength": 5,
          "sepalWidth": 3.4,
          "species": "setosa"
         },
         {
          "petalLength": 1.4,
          "petalWidth": 0.2,
          "sepalLength": 4.4,
          "sepalWidth": 2.9,
          "species": "setosa"
         },
         {
          "petalLength": 1.5,
          "petalWidth": 0.1,
          "sepalLength": 4.9,
          "sepalWidth": 3.1,
          "species": "setosa"
         },
         {
          "petalLength": 1.5,
          "petalWidth": 0.2,
          "sepalLength": 5.4,
          "sepalWidth": 3.7,
          "species": "setosa"
         },
         {
          "petalLength": 1.6,
          "petalWidth": 0.2,
          "sepalLength": 4.8,
          "sepalWidth": 3.4,
          "species": "setosa"
         },
         {
          "petalLength": 1.4,
          "petalWidth": 0.1,
          "sepalLength": 4.8,
          "sepalWidth": 3,
          "species": "setosa"
         },
         {
          "petalLength": 1.1,
          "petalWidth": 0.1,
          "sepalLength": 4.3,
          "sepalWidth": 3,
          "species": "setosa"
         },
         {
          "petalLength": 1.2,
          "petalWidth": 0.2,
          "sepalLength": 5.8,
          "sepalWidth": 4,
          "species": "setosa"
         },
         {
          "petalLength": 1.5,
          "petalWidth": 0.4,
          "sepalLength": 5.7,
          "sepalWidth": 4.4,
          "species": "setosa"
         },
         {
          "petalLength": 1.3,
          "petalWidth": 0.4,
          "sepalLength": 5.4,
          "sepalWidth": 3.9,
          "species": "setosa"
         },
         {
          "petalLength": 1.4,
          "petalWidth": 0.30000000000000004,
          "sepalLength": 5.1,
          "sepalWidth": 3.5,
          "species": "setosa"
         },
         {
          "petalLength": 1.7000000000000002,
          "petalWidth": 0.30000000000000004,
          "sepalLength": 5.7,
          "sepalWidth": 3.8,
          "species": "setosa"
         },
         {
          "petalLength": 1.5,
          "petalWidth": 0.30000000000000004,
          "sepalLength": 5.1,
          "sepalWidth": 3.8,
          "species": "setosa"
         },
         {
          "petalLength": 1.7000000000000002,
          "petalWidth": 0.2,
          "sepalLength": 5.4,
          "sepalWidth": 3.4,
          "species": "setosa"
         },
         {
          "petalLength": 1.5,
          "petalWidth": 0.4,
          "sepalLength": 5.1,
          "sepalWidth": 3.7,
          "species": "setosa"
         },
         {
          "petalLength": 1,
          "petalWidth": 0.2,
          "sepalLength": 4.6,
          "sepalWidth": 3.6,
          "species": "setosa"
         },
         {
          "petalLength": 1.7000000000000002,
          "petalWidth": 0.5,
          "sepalLength": 5.1,
          "sepalWidth": 3.3,
          "species": "setosa"
         },
         {
          "petalLength": 1.9,
          "petalWidth": 0.2,
          "sepalLength": 4.8,
          "sepalWidth": 3.4,
          "species": "setosa"
         },
         {
          "petalLength": 1.6,
          "petalWidth": 0.2,
          "sepalLength": 5,
          "sepalWidth": 3,
          "species": "setosa"
         },
         {
          "petalLength": 1.6,
          "petalWidth": 0.4,
          "sepalLength": 5,
          "sepalWidth": 3.4,
          "species": "setosa"
         },
         {
          "petalLength": 1.5,
          "petalWidth": 0.2,
          "sepalLength": 5.2,
          "sepalWidth": 3.5,
          "species": "setosa"
         },
         {
          "petalLength": 1.4,
          "petalWidth": 0.2,
          "sepalLength": 5.2,
          "sepalWidth": 3.4,
          "species": "setosa"
         },
         {
          "petalLength": 1.6,
          "petalWidth": 0.2,
          "sepalLength": 4.7,
          "sepalWidth": 3.2,
          "species": "setosa"
         },
         {
          "petalLength": 1.6,
          "petalWidth": 0.2,
          "sepalLength": 4.8,
          "sepalWidth": 3.1,
          "species": "setosa"
         },
         {
          "petalLength": 1.5,
          "petalWidth": 0.4,
          "sepalLength": 5.4,
          "sepalWidth": 3.4,
          "species": "setosa"
         },
         {
          "petalLength": 1.5,
          "petalWidth": 0.1,
          "sepalLength": 5.2,
          "sepalWidth": 4.1,
          "species": "setosa"
         },
         {
          "petalLength": 1.4,
          "petalWidth": 0.2,
          "sepalLength": 5.5,
          "sepalWidth": 4.2,
          "species": "setosa"
         },
         {
          "petalLength": 1.5,
          "petalWidth": 0.2,
          "sepalLength": 4.9,
          "sepalWidth": 3.1,
          "species": "setosa"
         },
         {
          "petalLength": 1.2,
          "petalWidth": 0.2,
          "sepalLength": 5,
          "sepalWidth": 3.2,
          "species": "setosa"
         },
         {
          "petalLength": 1.3,
          "petalWidth": 0.2,
          "sepalLength": 5.5,
          "sepalWidth": 3.5,
          "species": "setosa"
         },
         {
          "petalLength": 1.4,
          "petalWidth": 0.1,
          "sepalLength": 4.9,
          "sepalWidth": 3.6,
          "species": "setosa"
         },
         {
          "petalLength": 1.3,
          "petalWidth": 0.2,
          "sepalLength": 4.4,
          "sepalWidth": 3,
          "species": "setosa"
         },
         {
          "petalLength": 1.5,
          "petalWidth": 0.2,
          "sepalLength": 5.1,
          "sepalWidth": 3.4,
          "species": "setosa"
         },
         {
          "petalLength": 1.3,
          "petalWidth": 0.30000000000000004,
          "sepalLength": 5,
          "sepalWidth": 3.5,
          "species": "setosa"
         },
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",
      "text/plain": [
       "<VegaLite 2 object>\n",
       "\n",
       "If you see this message, it means the renderer has not been properly enabled\n",
       "for the frontend that you are using. For more information, see\n",
       "https://altair-viz.github.io/user_guide/troubleshooting.html\n"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "alt.Chart(iris).mark_circle().encode(\n",
    "    x='petalLength',\n",
    "    y='sepalWidth',\n",
    "    color='species'\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
